Omnichannel Intelligence in Gaming: AI and Mobile Systems for Casino Slot Transformation

Authors

DOI:

https://doi.org/10.26438/ijcse/v13i7.2733

Keywords:

Artificial Intelligence, Personalization

Abstract

This paper explores a transformative mobile ecosystem for casino slot management, blending AI-driven personalization, predictive analytics, decentralized identity, and secure cloud-native infrastructure. The proposed framework enhances operational efficiency, data privacy, and player experience through multimodal biometric authentication, personalized offer engines, predictive dispatch, and hybrid AI-cloud architecture. By addressing the limitations of legacy systems and unifying mobile and physical gaming experiences, the system fosters zero-friction interaction, real-time insight, and responsible gambling.

References

[1] M. Jones and P. Smith, "The Digital Transformation of the Gaming Industry: A Review of Emerging Technologies and Consumer Behavior," Journal of Casino Technology and Innovation, Vol.15, No.2, pp.123–135, 2023.

[2] J. C. Corbett et al., "Spanner: Google`s globally-distributed database," OSDI, 2012.

[3] Z. Dehghani, Data Mesh: Delivering Data-Driven Value at Scale. O`Reilly Media, 2020.

[4] C. Dwork, F. McSherry, K. Nissim, and A. Smith, "Calibrating noise to sensitivity in private data analysis," in Theory of Cryptography Conference, 2006.

[5] C. Gentry, "Fully homomorphic encryption using ideal lattices," STOC, 2009.

[6] A. C. Yao, "How to generate and exchange secrets," in Foundations of Computer Science, 1986.

[7] A. B. Chen, "Advanced Predictive Analytics in Casino Marketing: Leveraging Big Player Data for Hyper-Personalization and Churn Prevention," IEEE Transactions on Gaming Analytics and Player Engagement, Vol.8, No.4, pp.201–210, 2022.

[8] C. D. White and E. F. Green, "Real-time Optimization of Hospitality Services Using Machine Learning and Dynamic Resource Allocation," International Journal of Hospitality Management Systems and Operations Research, Vol.20, No.1, pp.45–58, 2024.

[9] G. H. Black, "The Role of Intelligent User Interfaces in Enhancing Player Engagement and Satisfaction in Digital and Physical Gaming Environments," Gaming UX Quarterly, Vol.5, No.3, pp.88–99, 2023.

[10] L. M. Brown, "QR Code Adoption, Security Protocols, and User Acceptance in the Modern Service Industry: A Comprehensive Study," Journal of Mobile Commerce Research and Applications, Vol.12, No.1, pp.5–18, 2023.

[11] N. P. Miller, "AI in Staff Dispatch and Workforce Optimization: Case Studies from High-Volume Service Industries," AI & Operations Research Journal, Vol.7, No.2, pp.77–88, 2024.

[12] O. Q. Davis, "Legal and Ethical Considerations of Data Pooling and Aggregation in Consumer Loyalty Programs: Balancing Personalization and Privacy," Journal of Consumer Data Privacy and Digital Ethics, Vol.4, No.1, pp.30–45, 2023.

[13] P. R. Chen and S. K. Lim, "Reinforcement Learning for Dynamic Pricing and Revenue Management in the Hospitality Sector," Annals of Tourism Research, Vol.55, pp.101-115, 2023.

[14] Q. S. Wong and V. T. Lee, "The Impact of Ubiquitous Mobile Technology on Customer Experience in Integrated Resorts," International Journal of Contemporary Hospitality Management, Vol.35, No.1, pp.200-215, 2023.

[15] U. V. Singh and W. X. Patel, "Edge Computing Architectures for Real-time Personalization in Smart Environments," Journal of Pervasive Computing and Communications, Vol.18, No.3, pp.220-235, 2024.

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Published

2025-07-31
CITATION
DOI: 10.26438/ijcse/v13i7.2733
Published: 2025-07-31

How to Cite

[1]
K. Ramachandran, “Omnichannel Intelligence in Gaming: AI and Mobile Systems for Casino Slot Transformation”, Int. J. Comp. Sci. Eng., vol. 13, no. 7, pp. 27–33, Jul. 2025.

Issue

Section

Research Article